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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Recently, the use of diverse renewable energy resources has been intensively expanding due to their technical and environmental benefits. One of the important issues in the modeling and simulation of renewable energy resources is the extraction of the unknown parameters in photovoltaic models. In this regard, the parameters of three models of photovoltaic (PV) cells are extracted in this paper with a new optimization method called turbulent flow of water-based optimization (TFWO). The applications of the proposed TFWO algorithm for extracting the optimal values of the parameters for various PV models are implemented on the real data of a 55 mm diameter commercial R.T.C. France solar cell and experimental data of a KC200GT module. Further, an assessment study is employed to show the capability of the proposed TFWO algorithm compared with several recent optimization techniques such as the marine predators algorithm (MPA), equilibrium optimization (EO), and manta ray foraging optimization (MRFO). For a fair performance evaluation, the comparative study is carried out with the same dataset and the same computation burden for the different optimization algorithms. Statistical analysis is also used to analyze the performance of the proposed TFWO against the other optimization algorithms. The findings show a high closeness between the estimated power–voltage (P–V) and current–voltage (I–V) curves achieved by the proposed TFWO compared with the experimental data as well as the competitive optimization algorithms, thanks to the effectiveness of the developed TFWO solution mechanism.

Details

Title
Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer
Author
Mokhtar, Said 1   VIAFID ORCID Logo  ; Shaheen, Abdullah M 2 ; Ginidi, Ahmed R 2   VIAFID ORCID Logo  ; El-Sehiemy, Ragab A 3   VIAFID ORCID Logo  ; Karar Mahmoud 4   VIAFID ORCID Logo  ; Lehtonen, Matti 5   VIAFID ORCID Logo  ; Darwish, Mohamed M F 6   VIAFID ORCID Logo 

 Department of Electrical Engineering, Faculty of Engineering, Fayoum University, 43518 Fayoum, Egypt; [email protected] 
 Department of Electrical Engineering, Faculty of Engineering, Suez University, 41522 Suez, Egypt; [email protected] (A.M.S.); [email protected] (A.R.G.) 
 Department of Electrical Engineering, Faculty of Engineering, Kafrelshiekh University, 33516 Kafrelshiekh, Egypt; [email protected] 
 Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland; [email protected] (K.M.); [email protected] (M.L.); Department of Electrical Engineering, Faculty of Engineering, Aswan University, 81542 Aswan, Egypt 
 Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland; [email protected] (K.M.); [email protected] (M.L.) 
 Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland; [email protected] (K.M.); [email protected] (M.L.); Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, 11629 Cairo, Egypt 
First page
627
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
22279717
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2530148564
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.